{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T07:47:49Z","timestamp":1760255269836},"reference-count":28,"publisher":"MIT Press - Journals","issue":"1","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Neural Computation"],"published-print":{"date-parts":[[2001,1,1]]},"abstract":"<jats:p> The synaptic phenomena of long-term potentiation (LTP) and long-term depression (LTD) have been intensively studied for over twenty-five years. Although many diverse aspects of these forms of plasticity have been observed, no single theory has offered a unifying explanation for them. Here, a statistical \u201cbin\u201d model is proposed to account for a variety of features observed in LTP and LTD experiments performed with field potentials in mammalian cortical slices. It is hypothesized that long-term synaptic changes will be induced when statistically unlikely conjunctions of pre- and postsynaptic activity occur. This hypothesis implies that finite changes in synaptic strength will be proportional to information transmitted by conjunctions and that excitatory synapses will obey a Hebbian rule (Hebb, 1949). Using only one set of constants, the bin model offers an explanation as to why synaptic strength decreases in a decelerating manner during LTD induction (Mulkey &amp; Malenka, 1992); why the induction protocols for LTP and LTD are asymmetric (Dudek &amp; Bear, 1992; Mulkey &amp; Malenka, 1992); why stimulation over a range of frequencies produces a frequency-response curve similar to that proposed by the BCM theory (Bienenstock, Cooper, &amp; Munro, 1982; Dudek &amp; Bear, 1992); and why this curve would shift as postsynaptic activity is changed (Kirkwood, Rioult, &amp; Bear, 1996). In addition, the bin model offers an alternative to the BCM theory by predicting that changes in postsynaptic activity will produce vertical shifts in the curve rather than merely horizontal shifts. <\/jats:p>","DOI":"10.1162\/089976601300014646","type":"journal-article","created":{"date-parts":[[2002,7,27]],"date-time":"2002-07-27T11:55:01Z","timestamp":1027770901000},"page":"87-111","source":"Crossref","is-referenced-by-count":9,"title":["A Statistical Theory of Long-Term Potentiation and Depression"],"prefix":"10.1162","volume":"13","author":[{"given":"John M.","family":"Beggs","sequence":"first","affiliation":[{"name":"National Institute of Mental Health, Lab of Neural Network Physiology, Bethesda, MD 20892-4075, U.S.A."}]}],"member":"281","reference":[{"key":"p_1","doi-asserted-by":"publisher","DOI":"10.1126\/science.3037696"},{"key":"p_4","doi-asserted-by":"publisher","DOI":"10.1523\/JNEUROSCI.18-24-10464.1998"},{"key":"p_5","doi-asserted-by":"publisher","DOI":"10.1523\/JNEUROSCI.02-01-00032.1982"},{"key":"p_6","doi-asserted-by":"publisher","DOI":"10.1113\/jphysiol.1973.sp010273"},{"key":"p_7","doi-asserted-by":"publisher","DOI":"10.1038\/361031a0"},{"key":"p_8","doi-asserted-by":"publisher","DOI":"10.1098\/rspb.1969.0087"},{"key":"p_9","doi-asserted-by":"publisher","DOI":"10.1152\/jn.1991.66.5.1785"},{"key":"p_10","doi-asserted-by":"publisher","DOI":"10.1523\/JNEUROSCI.19-02-00836.1999"},{"key":"p_11","doi-asserted-by":"publisher","DOI":"10.1152\/jn.1994.72.3.1220"},{"key":"p_12","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.89.10.4363"},{"key":"p_14","doi-asserted-by":"publisher","DOI":"10.1126\/science.1346729"},{"key":"p_16","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.83.14.5326"},{"key":"p_17","doi-asserted-by":"publisher","DOI":"10.1523\/JNEUROSCI.14-03-01634.1994"},{"key":"p_18","doi-asserted-by":"publisher","DOI":"10.1126\/science.8502997"},{"key":"p_19","doi-asserted-by":"publisher","DOI":"10.1038\/381526a0"},{"key":"p_20","doi-asserted-by":"publisher","DOI":"10.1109\/2.36"},{"key":"p_21","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.86.23.9574"},{"key":"p_22","doi-asserted-by":"publisher","DOI":"10.1098\/rspb.1970.0040"},{"key":"p_24","doi-asserted-by":"publisher","DOI":"10.1016\/0896-6273(92)90248-C"},{"key":"p_25","doi-asserted-by":"publisher","DOI":"10.1038\/7263"},{"key":"p_26","doi-asserted-by":"publisher","DOI":"10.1002\/j.1538-7305.1948.tb00917.x"},{"key":"p_27","doi-asserted-by":"publisher","DOI":"10.1016\/0006-8993(90)91830-A"},{"key":"p_28","doi-asserted-by":"publisher","DOI":"10.1016\/0006-8993(76)90573-4"},{"key":"p_29","doi-asserted-by":"publisher","DOI":"10.1016\/0022-5193(70)90128-1"},{"key":"p_31","doi-asserted-by":"publisher","DOI":"10.1523\/JNEUROSCI.17-20-07926.1997"},{"key":"p_32","doi-asserted-by":"publisher","DOI":"10.1152\/jn.1999.82.4.2024"},{"key":"p_33","doi-asserted-by":"publisher","DOI":"10.1038\/387497a0"},{"key":"p_34","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.87.17.6718"}],"container-title":["Neural Computation"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mitpressjournals.org\/doi\/pdf\/10.1162\/089976601300014646","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,3,12]],"date-time":"2021-03-12T21:48:43Z","timestamp":1615585723000},"score":1,"resource":{"primary":{"URL":"https:\/\/direct.mit.edu\/neco\/article\/13\/1\/87-111\/6451"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2001,1,1]]},"references-count":28,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2001,1,1]]}},"alternative-id":["10.1162\/089976601300014646"],"URL":"https:\/\/doi.org\/10.1162\/089976601300014646","relation":{},"ISSN":["0899-7667","1530-888X"],"issn-type":[{"value":"0899-7667","type":"print"},{"value":"1530-888X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2001,1,1]]}}}